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dc.creatorHuffaker, Rayes_ES
dc.creatorMuñoz Carpena, Rafaeles_ES
dc.creatorCampo-Bescós, Migueles_ES
dc.creatorSouthworth, Janees_ES
dc.description.abstractThere are increasing calls to audit decision-support models used for environmental policy to ensure that they correspond with the reality facing policy makers. Modelers can establish correspondence by providing empirical evidence of real-world behavior that their models skillfully simulate. Since real-world behavior—especially in environmental systems—is often complex, credibly modeling underlying dynamics is essential. We present a pre-modeling diagnostic framework based on Nonlinear Time Series (NLTS) methods for reconstructing real-world environmental dynamics from observed data. The framework is illustrated with a case study of saltwater intrusion into coastal wetlands in Everglades National Park, Florida, USA. We propose that environmental modelers test for systematic dynamic behavior in observed data before resorting to conventional stochastic exploratory approaches unable to detect this valuable information. Reconstructed data dynamics can be used, along with other expert information, as a rigorous benchmark to guide specification and testing of environmental decision-support models corresponding with real-world behavior.en
dc.description.sponsorshipRH acknowledges support from NIFA (FLA-ABE-005414), RMC acknowledges support from the UF Water Institute Faculty Fellowship.en
dc.format.extent42 p.
dc.relation.ispartofEnvironmental Modelling & Software, 83 (2016) 74-87en
dc.rights© 2016 Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0en
dc.subjectModel evaluationen
dc.subjectNonlinear dynamicsen
dc.subjectPhase space reconstructionen
dc.subjectExtreme value statisticsen
dc.titleDemonstrating correspondence between decision-support models and dynamics of real-world environmental systemsen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentProyectos e Ingeniería Rurales_ES
dc.contributor.departmentLanda Ingeniaritza eta Proiektuakeu
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.type.versionVersión aceptada / Onetsi den bertsioaes

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© 2016 Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0
Except where otherwise noted, this item's license is described as © 2016 Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0

El Repositorio ha recibido la ayuda de la Fundación Española para la Ciencia y la Tecnología para la realización de actividades en el ámbito del fomento de la investigación científica de excelencia, en la Línea 2. Repositorios institucionales (convocatoria 2020-2021).
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